Moore Positioning Findings - AFPS Tracker

The framework-selection gate was approved earlier (compiled YAML, approval_status: ready-for-agent-review) — that is the Stage-1 scope approval for the whole selected set, so moore-positioning enters directly at its research stage. Frameworks 1 (jtbd-positioning) and 2 (strategic-canvas) are complete and their intermediates are written; this session ran the final pending framework, moore-positioning, inline.

The Geoffrey Moore “Crossing the Chasm” template, filled from approved evidence. Each blank is graded for evidence quality in the next section.

Compressed claim: AFPS Tracker is the passive, source-of-truth-preserving way to stay in command of a multi-branch AI research portfolio — navigable like a board, faithful like the files.

Confidence per template element. The chart shows relative evidence strength; the full status + source table follows (open with “View as table”).

Status key: Evidenced = directly supported by approved research artifacts; Hypothesized = reasonable inference, not directly confirmed; Unvalidated = assertion without supporting evidence.

Weakest element: Market category

• Why it’s weak. Moore’s template treats category as the frame buyers use to find and evaluate a product. Here there is no established category and no search term: the canvas concluded “no existing category cleanly fits,” competitive analysis found no validated public AFPS-native competitor, and Stage-0 interrogation could only offer a provisional internal label (“AFPS workflow-state tracker”). A position whose category is invented is hard to discover and easy to mis-evaluate.
• What would change if wrong. If buyers reach for an existing frame (generic PM, research repository, agent memory) the product gets compared on that frame’s terms — breadth, collaboration, execution — exactly the red-ocean axes where the deliberate “Low” scores read as missing features instead of discipline. Mis-framing turns the wedge into a weakness.
• Evidence needed. Discovery interviews on the words operators actually use for this pain; whether they expect a “tool” at all or treat it as a native-files problem; whether a borrowed anchor (“portfolio tracker for AI research workflows”) aids comprehension without inviting PM expectations.
• Cost of being wrong. High for go-to-market (invisible or mis-shelved); moderate for the product itself (the differentiator still holds even if the label changes).

Second weakest: existence + urgency of the target/need at scale

Not a template-wording problem but the deepest risk. The target customer and need are well-evidenced from artifacts but not user-tested: whether AFPS operators exist beyond dogfooding, and whether multi-path pain clears the bar to fire free native files, remains the existential open question (icp.md, journey-map, jtbd all flag it; WTP unproven).

Category-label alternatives considered (within this element)

Alternative 1: Studio / consultant decision-provenance frame

Why considered: strongest adjacent WTP (business budget, billable-time logic); provenance is a real social facet of the job. Why not preferred: studios are the adjacent ICP, not the approved primary; AFPS adoption among them is unproven; it over-weights the provenance/social facet jtbd explicitly marks secondary, pulling toward a client-reporting tool and away from the individual-operator wedge.

Alternative 2: Agent re-grounding / persistent-memory frame

Why considered: matches operator “context loss / keeping up with AI speed” language; the agent-re-grounding job is a genuine functional facet. Why not preferred: reframes the product as agent memory / control plane (Runshift territory), which jtbd and competitive analysis place out of approved scope; it inverts the human-legibility anchor and trades a clear wedge for a crowded execution-adjacent one. Keep as latent expansion, not the headline.

• No direct AFPS-operator interviews or observed switching sessions; the template is synthesized from approved artifacts, not live customer language.
• No measured reconstruction-time baseline, so the size of the need (and the benefit) is directional.
• No prototype test of the source-linked read-through (the predicted aha that underwrites benefit + differentiation).
• No direct WTP evidence; adjacent pricing is a budget signal only.
• Category framing is untested with real buyers — the single biggest template risk.
• No parser-fidelity audit; differentiation defensibility assumes reliable read-only parsing.

Cross-framework note (for parent synthesis, not routing): this is the final selected framework (3 of 3). The Moore template lands in a new/taught category, corroborating strategic-canvas’s “no category fits” finding and strengthening the case for synthesis to weigh whether to revisit category-design. This note does not itself invoke any skill.

approved Final compiled YAML (approval_status: ready-for-agent-review) was consumed on 2026-06-29. Recorded gate answers: template elements → approve all six as written; category treatment → carry the new/taught subcategory forward; research completeness → sufficient (carry as labeled hypothesis); format → good as-is; artifact destination → write intermediate, archive packet, confirm page. The parent loop applied:

No canonical research/afps-tracker/positioning.md is written by this framework. With all three intermediates now present, the next run enters synthesis (State B) and builds the unified positioning.md review page via /positioning --synthesize research/afps-tracker.

Review Gates

Each gate below requires one answer. “Other / None of the above” and “Need clarification” are always available; selecting them (or leaving a gate unanswered) keeps the response in not-approved.